How to store 7.3 billion rows of market data (optimized to be read)?

Question

I have a dataset of 1 minute data of 1000 stocks since 1998, that total around (2012-1998)*(365*24*60)*1000 = 7.3 Billion rows.

Most (99.9%) of the time

Answer 1

I think any major RDBMS would handle this. At the atomic level, a one table with correct partitioning seems reasonable (partition based on your data usage if fixed - this is ikely to be either symbol or date).

You can also look into building aggregated tables for faster access above the atomic level. For example if your data is at day, but you often get data back at the wekk or even month level, then this can be pre-calculated in an aggregate table. In some databases this can be done though a cached view (various names for different DB solutions - but basically its a view on the atomic data, but once run the view is cached/hardened intoa fixed temp table - that is queried for subsequant matching queries. This can be dropped at interval to free up memory/disk space).

I guess we could help you more with some idea as to the data usage.